Dongwei Ren

Computer Vision and Pattern Recognition · 2019–2022

A researcher in the Science corpus: 6 papers; trusts 660 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 234 citations into it; #10,883 of 21,575 by trust here, #6,089 by citations
• Artificial Intelligence — 94 citations into it; #18,720 of 35,345 by trust here, #10,942 by citations
• Media Technology — 53 citations into it
• Model Architectures — 19 citations into it
• Evaluation & Benchmarks — 15 citations into it
• Optimization & Training — 8 citations into it
• Radiology, Nuclear Medicine and Imaging — 8 citations into it; #1,497 of 3,265 by trust here, #1,115 by citations

Whom Dongwei Ren trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Kaiming He
3. Ross B. Girshick
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Yoshua Bengio
7. Jimmy Ba
8. Yann LeCun
9. Karen Simonyan
10. Ilya Sutskever

Who trusts Dongwei Ren overall

1. Syed Waqas Zamir
2. Jie Xiao
3. Aditya Arora
4. Chong Mou
5. Zhendong Wang
6. Hong Wang
7. Chunwei Tian
8. Jingyun Liang
9. Ziwei Luo
10. Salman Hameed Khan

Papers from Dongwei Ren's perspective

Ordered by how strongly the researchers Dongwei Ren trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Progressive Image Deraining Networks: A Better and Simpler Baseline (2019) — 1,016 citations
• Neural Blind Deconvolution Using Deep Priors (2019) — 332 citations
• Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression (2019) — 5,129 citations
• Localization Distillation for Object Detection (2022) — 94 citations
• Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation (2020) — 1,369 citations
• STAR: A Structure and Texture Aware Retinex Model (2019) — 297 citations